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Fitting mixed logit random regret minimization models using maximum simulated likelihood

Ziyue Zhu, Álvaro A. Gutiérrez-Vargas, Martina Vandebroek

arXiv 3 Jan 2023 · Econometrics · publishedThe Stata Journal Promoting communications on statistics and Stata (2024) · 1 citations (OpenAlex)

arXiv:2301.01091 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This article describes the mixrandregret command, which extends the randregret command introduced in Guti\'errez-Vargas et al. (2021, The Stata Journal 21: 626-658) incorporating random coefficients for Random Regret Minimization models. The newly developed command mixrandregret allows the inclusion of random coefficients in the regret function of the classical RRM model introduced in Chorus (2010, European Journal of Transport and Infrastructure Research 10: 181-196). The command allows the user to specify a combination of fixed and random coefficients. In addition, the user can specify normal and log-normal distributions for the random coefficients using the commands' options. The models are fitted using simulated maximum likelihood using numerical integration to approximate the choice probabilities.

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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Chorus, C. G (2010) A new model of random regret minimization0.51121100%
2Gutiérrez-Vargas, Á. A., M. Meulders, and M. Vandebroek (2021) randregret: A command for fitting random regret minimization models using Stata0.51121100%

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